ADAPTIVE NEURAL NETWORK STATE PREDICTOR AND TRACKING CONTROL FOR NONLINEAR TIME-DELAY SYSTEMS

被引：0

作者：

Na, Jing ^{[1
]}

Ren, Xuemei ^{[1
]}

Gao, Yan ^{[1
]}

Robert, Grino ^{[2
]}

Ramon, Costa-Castello ^{[2
]}

机构：

[1] Beijing Inst Technol, Educ Minist, Key Lab Complex Syst Intelligent Control & Decis, Dept Automat Control, Beijing 100081, Peoples R China

[2] Univ Politecn Cataluna, Inst Org & Control Sistemas Ind, Barcelona, Spain

来源：

INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL | 2010年 / 6卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Time-delay system; Neural network; State predictor; Feedback control; IDENTIFICATION;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A new adaptive nonlinear state predictor (ANSP) is presented for a class of unknown nonlinear systems with input time-delay. A dynamical identification with neural network (NN) is constructed to obtain. NN weights and their derivatives. The future NN weights are deduced for the nonlinear state predictor design without iterative calculations. The time-delay and unknown nonlinearity are compensated by a feedback control using the predicted states. Rigorous stability analysis for the identification, predictor and feedback control are provided by means of Lyapunov criterion. Simulations and practical experiments of a temperature control system are included to verify the effectiveness of the proposed scheme.

引用

页码：627 / 639

页数：13

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